Head of Data Analytics

1 week ago


Bengaluru, Karnataka, India Simply Vyapar Apps Private Limited Full time

About Vyapar:

We are a technology and innovation company in the fintech space, delivering business accounting software to Micro, Small & Medium Enterprises (MSMEs). With over 10 million users across 140 countries, we are one of the fastest-growing companies in this space. We simplify invoicing, inventory management & accounting, allowing small businesses to focus on high-value tasks rather than manual bookkeeping.

**Job Summary:**

As the Head of Data Analytics & Data Science, you will lead our data-driven strategy and insights generation. You will oversee a talented team of data analysts and scientists, ensuring we harness data to inform business decisions, optimize product features, and enhance user experience. You will collaborate with cross-functional teams to drive actionable insights.

**Key Responsibilities:**

• Develop and execute a comprehensive data analytics and data science strategy aligned with Vyapar's business objectives.

• Lead, mentor, and grow a high-performing team of data professionals.

• Oversee the collection, processing, and analysis of large datasets to derive actionable insights. Ensure data integrity, security, and compliance across all analytics initiatives.

• Identify key metrics and KPIs to track business performance and user engagement. Develop predictive models and advanced analytics solutions to inform product development and marketing strategies.

• Collaborate with product, engineering, and marketing teams to translate data insights into product improvements and marketing strategies. Communicate findings and recommendations effectively to stakeholders at all levels.

**Requirements:**

• Master's degree in data science, statistics, mathematics, computer science, or a related field.

• 10 to 15 years of experience in data analytics and data science, with a proven track record in a leadership role. Experience in a tech startup or SaaS environment is a plus.

• Proficiency in programming languages (e.g., Python, R), SQL, and familiarity with big data technologies (e.g., Hadoop, Spark) and data visualization tools (e.g., Tableau, Power BI).

• Strong understanding of statistical analysis, machine learning algorithms, and data mining techniques.

• Excellent verbal and written communication skills, with the ability to present complex data insights to diverse audiences.



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